AI App Development
LLM features and internal automation that solve a specific, measurable problem instead of demoing well and dying.
Claude · OpenAI · LangGraph · pgvector
Python · Backend & AI
Python development for AI, data and automation.
FastAPI services, data pipelines and LLM integrations written as production software: typed, tested and deployed through the same pipeline as everything else.
Python · Backend & AI
What we build
What we build with Python.
AI services
Retrieval pipelines, agents and model gateways exposed as clean APIs to the rest of your product.
Data pipelines
Scheduled and event-driven jobs that ingest, clean and load data, with monitoring when they fail.
Back-office automation
Scripts and services that replace manual reporting, reconciliation and document handling.
APIs and admin systems
FastAPI and Django backends with typed contracts and generated documentation.
The difference
When Python is the right call.
No tool fits everything. We would rather tell you now than halfway through the build.
Consider something else
- Front-end heavy products where sharing TypeScript types matters more
- Ultra-low-latency services better written in a compiled language
A strong fit
- AI and LLM-powered features
- Data pipelines, ETL and reporting
- Automation of internal back-office processes
- Scientific, numerical or document-processing workloads
How we use it
Practices we hold ourselves to.
Knowing a framework is the easy part. These are the habits that keep a codebase healthy after a year of changes.
Typed Python
Type hints and Pydantic models throughout, checked in CI, so refactoring is safe.
Reproducible environments
Locked dependencies and container builds, so it runs the same on a laptop and in production.
Evaluations for AI code
Model-dependent behaviour covered by scored evaluation sets, alongside ordinary unit tests.
Pipelines that fail loudly
Retries, dead-letter handling and alerts, so a broken job is noticed the same day.
Ecosystem
What we pair with Python.
- Web
- FastAPI
- Django
- Pydantic
- SQLAlchemy
- AI
- Anthropic SDK
- OpenAI SDK
- LangGraph
- pgvector
- Data
- Pandas
- Polars
- dbt
- Airflow
- Operations
- uv
- Docker
- pytest
- Celery
Engagements
Three ways to get Python work done.
Hand us the whole build, or add senior engineers to the team you already have.
Discovery sprint
From $2,500
1–2 weeks
You have a problem and need a plan you can act on or take elsewhere.
- Stakeholder and user interviews
- Technical feasibility review
- Scoped roadmap with estimates
- Clickable prototype of the core flow
Most common
Build engagement
Fixed-scope quote
6–16 weeks
You know what you need built and want it shipped by a senior team.
- Design, engineering and QA
- Two-week sprints with working demos
- CI/CD, monitoring and store submission
- Documentation and handover session
Embedded team
Monthly retainer
Rolling, 30 days' notice
You have an in-house team and need senior capacity beside it.
- Dedicated engineers in your standups
- Code review and architecture support
- Roadmap and sprint planning input
- Pause or stop with 30 days' notice
Services
Services where we use Python.
Full-Stack Web Development
Marketing sites, dashboards and web apps built on a modern stack that stays fast as the feature list grows.
Next.js · TypeScript · Node.js · PostgreSQL
DevOps & Cloud
Pipelines, infrastructure and monitoring that let a small team release daily without anyone holding their breath.
AWS · Terraform · Docker · Kubernetes
FAQ
Python: common questions.
FastAPI or Django?
FastAPI for API services and AI backends, where its typing and async support shine. Django when you want an admin interface, an ORM and conventions out of the box for a content- or data-heavy application.
Can Python services sit alongside our Node.js backend?
Yes, and it is a common setup: Node.js serving the product API, Python handling AI and data work, with a typed contract between them.
Can you productionise a data scientist's notebook?
Yes. We turn exploratory code into a tested, deployable service with input validation, monitoring and a repeatable environment.
Do you do model training?
Occasionally, where evaluations show it is needed. Most business problems are better solved with retrieval and a strong general model, which is cheaper to build and maintain.
Next step
Have something that needs building?
Tell us the problem in a few sentences. We will reply within one business day with an honest read on scope, cost and whether we are the right team for it.